Impact of Query Specification Mode and Problem Complexity on Query Specification Productivity of Novice Users of Database Systems

With the increased demand for the utilization of computerized information systems by business users, the need for investigating the impact of various user interfaces has been well recognized. It is usually assumed that providing the user with assistance in the usage o-f a system would significantly increase the user's productivity. There is, however, a dearth of systematic inquiry into this commonly held notion to verify its validity in a scientific fashion. The purpose of this study is to investigate the impact of system-provided user assistance and complexity level of the problem on novice users' productivity in specifying database queries. The study is theoretical in the sense that it presents an approach adopted from research in deductive database systems to attack problems concerning user interface design. It is empirical in that it conducts an experiment in a controlled laboratory setting to collect primary data for the testing of a series of hypotheses. The two independent variables are system-provided user assistance and problem complexity, while the dependent variable is the user's query specification productivity. Three measures are used as separate indicators of query specification productivity: number of syntactic errors, number of semantic errors, and time required for completing a query task. Due to the lack of a well-defined metric for user assistance, the study first presents a generic classification scheme for relational query specification. Based on this classification scheme, two quantitative metrics for measuring the amount of user assistance in terms of prompts and defaults were developed. The user assistance is operationally defined with these two metrics. Four findings emerge as significant results of the study. First, user assistance has a significant main effect on all of the three dependent measures at the 1 percent significance level. Second, problem complexity also has a significant impact on the three productivity measures at the 1 percent significance level. Third, the interaction effect of user assistance and problem complexity on the number of semantic errors and the amount of time for completion is significant at the 1 percent level. Fourth, Although this interaction effect on the number of syntactic errors is not significant at the 5 percent level, it is at the 10 percent level. More research is needed to permit a thorough understanding of the issue of user interface design. A list of topics is suggested for future research to confirm or to modify the findings of this study

A FIELD EVALUATION OF NATURAL LANGUAGE FOR DATA RETRIEVAL

Although a large number of natural language database interfaces have been developed, there have been few empirical studies of their practical usefulness. This paper presents the design and results of a field evaluation of a natural language system - NLS - used for data retrieval . A balanced, multifactorial design comparing NLS with a reference retrieval language, SQL, is described. The data are analyzed on two levels: work task (n=87) and query (n=1081). SQL performed better than NLS on a variety of measures, but NLS required less effort to use. Subjects performed much poorer than expected based on the results of laboratory studies. This finding is attributed to the complexity of the field setting and to optimism in grading laboratory experiments. The methodology developed for studying computer languages in real work settings was successful in consistently measuring differences in treatments over a variety of conditions.Information Systems Working Papers Serie

Database system architecture supporting coexisting query languages and data models

SIGLELD:D48239/84 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

SQL pattern design, development & evaluation of its efficacy

Databases provide the foundation of most software systems. This means that system developers will inevitably need to write code to query these databases. The de facto language for querying is SQL and this, consequently, is the language primarily taught by higher education institutions. There is some evidence that learners find it hard to master SQL. These issues and concerns were confirmed by reviewing the literature and establishing the scope and context. The literature review allowed extraction of the common issues in impacting SQL acquisition. The identified issues were confirmed and justified by empirical evidence as reported here. A model of SQL learning was derived. This framework or model involves SQL learning taxonomy, a model of SQL problem solving and incorporates cross-cutting factors. The framework is used as map to the design of a proposed instructional design. The design employed pattern concepts and the related research to structure SQL knowledge as SQL patterns. Also presented are details on how SQL patterns could be organized and presented. A strong theoretical background (checklist, component-level design) was employed to organize, present and facilitated SQL pattern collection. The evaluation of the SQL patterns yielded new insight such as novice problem solving strategies and the types of errors students made in attempting to solve SQL problems. SQL patterns, as proposed as a result of this research, yielded statistically significant important in novice performance in writing SQL queries. A longitudinal field study with a large number of learners in a flexible environment should be conducted to confirm the findings of this research